Abstract The production of concrete, a major construction material, emits a large amount of CO2 from the material production stage, such as in the production of cement, aggregates, and admixtures, to the manufacturing stage, and it is expected that a reduction of CO2 emission will be required. Acco...
Abstract The production of concrete, a major construction material, emits a large amount of CO2 from the material production stage, such as in the production of cement, aggregates, and admixtures, to the manufacturing stage, and it is expected that a reduction of CO2 emission will be required. Accordingly, a study on the assessment of the appropriate amount of CO2 emission in the concrete production is necessary. As a result, in environmentally developed countries, studies have been conducted on the production of low-CO2-emitting concrete, such as a low-carbon concrete procurement system, but studies on this topic have been insufficient in Korea. Therefore, this study evaluated the appropriateness and the reduction performance of the low-carbon-emission concrete (LCEC) mix design system and the deduced mix design results using an evolutionary algorithm (EA), the optimal mix design method, which minimizes the CO2 emission of the concrete mix design. This study established a mix design database from approximately 800 concrete mix designs with different strengths and used an EA to deduce the optimal mix design. When deducing the optimal mix design, we considered design variables, object functions, and constraint functions to develop the algorithm. Then, the appropriateness and reliability of the mix design deduced from the optimal LCEC mix design system, which in turn was developed by using the above algorithm, were evaluated. Additionally, case studies of current structures in Korea were divided into the actual concrete mix designs and the deduced optimal mix designs, which were compared to analyze the CO2 emissions. According to the case study of the concrete mix design deduced from this assessment system, the CO2 emissions of the optimal mix design compared to the actual mix design were reduced by 4 and 7% for 24 and 30MPa concrete, respectively.
Abstract The production of concrete, a major construction material, emits a large amount of CO2 from the material production stage, such as in the production of cement, aggregates, and admixtures, to the manufacturing stage, and it is expected that a reduction of CO2 emission will be required. Accordingly, a study on the assessment of the appropriate amount of CO2 emission in the concrete production is necessary. As a result, in environmentally developed countries, studies have been conducted on the production of low-CO2-emitting concrete, such as a low-carbon concrete procurement system, but studies on this topic have been insufficient in Korea. Therefore, this study evaluated the appropriateness and the reduction performance of the low-carbon-emission concrete (LCEC) mix design system and the deduced mix design results using an evolutionary algorithm (EA), the optimal mix design method, which minimizes the CO2 emission of the concrete mix design. This study established a mix design database from approximately 800 concrete mix designs with different strengths and used an EA to deduce the optimal mix design. When deducing the optimal mix design, we considered design variables, object functions, and constraint functions to develop the algorithm. Then, the appropriateness and reliability of the mix design deduced from the optimal LCEC mix design system, which in turn was developed by using the above algorithm, were evaluated. Additionally, case studies of current structures in Korea were divided into the actual concrete mix designs and the deduced optimal mix designs, which were compared to analyze the CO2 emissions. According to the case study of the concrete mix design deduced from this assessment system, the CO2 emissions of the optimal mix design compared to the actual mix design were reduced by 4 and 7% for 24 and 30MPa concrete, respectively.
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